A New Conway Maxwell–Poisson Liu Regression Estimator—Method and Application

Table 7

Estimated MSEs of the COMPRM estimators, when and .

n	ρ	MLE
50	0.80	12.499	3.380	4.104	9.078	2.425	3.265	3.339	7.266	2.425	3.075	2.780	7.266	2.425
	0.90	21.315	4.702	5.883	15.449	2.228	3.872	3.691	11.357	2.210	3.359	2.737	11.357	2.198
	0.95	41.605	8.442	10.981	31.267	1.947	5.544	4.937	21.024	1.926	4.116	2.872	21.024	1.911
	0.99	214.382	50.858	62.094	184.77	1.930	19.107	16.032	99.820	1.142	10.705	5.276	99.820	1.090
100	0.80	8.377	2.584	2.798	5.615	2.399	2.619	2.678	5.099	2.399	2.665	2.505	5.099	2.399
	0.90	15.056	3.216	3.961	10.130	2.333	3.157	3.263	8.701	2.333	3.072	2.674	8.701	2.333
	0.95	26.917	4.628	5.468	18.535	2.018	4.037	3.632	14.981	2.013	3.486	2.579	14.981	2.005
	0.99	126.189	21.054	26.319	94.634	1.020	13.853	11.793	66.917	0.904	7.774	3.699	66.917	0.871
150	0.80	8.168	2.412	2.505	5.245	2.354	2.412	2.453	4.816	2.354	2.512	2.398	4.816	2.354
	0.90	16.612	3.148	3.716	11.066	2.365	3.183	3.177	9.674	2.365	3.178	2.644	9.674	2.365
	0.95	29.902	4.154	5.051	20.500	1.800	4.070	3.565	16.221	1.800	3.528	2.434	16.221	1.800
	0.99	157.077	25.444	28.331	123.676	1.215	16.414	13.380	84.299	0.774	8.662	3.947	84.299	0.731
200	0.80	7.813	2.420	2.552	4.983	2.368	2.436	2.502	4.691	2.368	2.528	2.427	4.691	2.368
	0.90	14.655	2.808	3.133	9.427	2.406	2.890	2.859	8.408	2.406	3.031	2.574	8.408	2.406
	0.95	29.0736	4.150	4.941	19.217	1.984	4.228	3.727	16.060	1.980	3.740	2.581	16.060	1.979
	0.99	138.995	19.705	22.767	108.465	0.959	14.770	12.609	74.044	0.744	8.119	3.809	74.044	0.725